1. Statement of the Technical Field
The invention is directed to the field of communications. In particular, the invention is directed to systems and methods for reducing bit error rates in digital chaotic spread spectrum communications systems.
2. Description of the Related Art
There are many types of communications systems known in the art, such as multiple access communications systems, low probability of intercept/low probability of detection (LPI/LPD) communications systems and spread spectrum communications systems. Many of these systems depend on constant energy symbol and/or spreading sequences. Other systems induce exploitable correlations via constant energy pulse shaping. Inherent to these constant energy pulse based waveforms, the signal energy transmitted is stationary for all practical purposes, meaning that the energy transmitted as a function of time is constant. Non-constant energy pulse spreading sequences, such as those used in coherent chaotic waveforms, have also been employed but require significantly more computational power to synchronize. However, communication signals employing non-constant energy pulse spreading sequences are typically more secure and robust to interferers.
Regardless of the type of communications system being used, one common issue in communications systems is how to minimize the bit error rate (BER). That is, what is the best method to combat errors in the recognition of individual bits in a communications stream. Bit errors are normally encountered because of the non-ideal signal transmission medium that distorts and degrades the transmitted signal; the rate of these errors decreases nonlinearly based on how the transmission channel distorts the signal and the ratio of the signal power to the noise power obtained at the receiver. In the case of digital systems, a low BER is obtained by a variety of mechanisms, including equalization, coherent combining of diverse received signals, forward error correction, interleaving, variable transmission power, and more generally transmission power margins. These measures are typically optimized when the transmitted energy per symbol is held constant. Further, there is a desire to have the capability of dynamically adjusting the symbol energy in response to a time varying environment.
Embodiments of the invention provide systems and methods for chaotic spread spectrum communications with reduced bit error rates. In a first embodiment of the invention, a method is provided for communicating a sequence of information symbols between a transmitter and a receiver using a chaotic sequence spread spectrum signal. The method includes generating identical sequences of chaotic chips at the transmitter and the receiver, the sequences of chips synchronized in time. The method also includes transmitting a sequence of information symbols in a signal using the sequence of chips generated at the transmitter, each of the information symbols in the signal having a variable duration of transmission based on a threshold symbol energy value and the chips generated at the transmitter. The method further includes extracting the sequence of information symbols from the transmitted signal, each of the information symbols in the transmitted signal extracted using the chips generated at the receiver and the threshold symbol energy value, and where the duration of transmission of each of the information symbols in the signal is a total duration of a selected number of the chips used for transmitting each information symbols, and where the number of the chips is selected for each of the information symbols to provide a total chip energy that is greater than or equal to the threshold symbol energy value.
In a second embodiment of the invention, a system for communicating a chaotic sequence spread spectrum signal is provided. The system includes a transmitter for transmitting a sequence of information symbols in a spread spectrum signal using a chaotic sequence of chips generated at the transmitter, each of the information symbols in the signal having a duration of transmission based on a threshold symbol energy value and the chips generated at the transmitter. The system also includes a receiver for extracting the sequence of information symbols from the transmitted signal, each of the information symbols in the transmitted signal extracted using a chaotic sequence of chips generated at the receiver and the threshold symbol energy value. In the system, the chaotic sequences of chips generated at the transmitter and the receiver are identical and synchronized in time, where the duration of transmission of each of the information symbols in the carrier is a total duration of a selected number of the chips used for transmitting each information symbols, and where the number of the chips is selected for each of the information symbols to provide a total chip energy that is greater than or equal to the threshold symbol energy value.
Embodiments will be described with reference to the following drawing figures, in which like numerals represent like items throughout the figures, and in which:
Embodiments of the invention provide a spread-spectrum communications system employing a spreading signal generated using chaotic sequences and having improved bit error rate (BER) performance. A chaotic sequence, as that term is used herein, is a signal sequence having a time varying value expressed in a digital form that has no discernible regularity or order. In particular, the various embodiments of the invention provide a chaotic communications system in which the amount of energy per transmitted symbol is dynamically adjusted to account for the varying amplitudes of the chaotic spreading signal used to encode the data signal. That is, a communications system that adjusts the number of chips of the chaotic spreading signal used to ensure that each symbol is transmitted using at least a minimum amount of symbol energy required for reliable symbol detection at a receiver. In the various embodiments of the invention, this is accomplished by varying the length of the chaotic spreading signal used to encode a particular symbol. In other words, rather than providing a fixed symbol period length for all symbols in the data signal, a varying symbol period length is provided for each symbol being transmitted. The resulting operation that significantly constrains the energy per symbol must be coherently repeated at the receiver for accurate reception.
The invention will now be described more fully hereinafter with reference to accompanying drawings, in which illustrative embodiments of the invention are shown. This invention, may however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. For example, the invention can be embodied as a method, a system, or a computer program product. Accordingly, the invention can take the form as an entirely hardware embodiment, an entirely software embodiment or a hardware/software embodiment.
Generation of Chaotic Sequences
One aspect of the invention provides for a digitally generated chaotic sequence for spectrally spreading data symbols by generating a sequence of chaotic chips. In this regard, it should be appreciated that the presence of any discernible pattern in a chaotic spreading sequence is much more difficult to identify as compared to patterns that emerge over time with conventional pseudo-random number sequences. As such, a chaotic spreading sequence is characterized by a greater degree of apparent randomness as compared to these conventional pseudo-random number sequences, providing a higher degree of security.
Referring now to
As will be understood by one of ordinary skill in the art, each of the N polynomial equations f0(x(nT)), . . . , fN-1(x(nT)) can be solved independently to obtain a respective solution. Each solution can be expressed as a residue number system (RNS) residue value using RNS arithmetic operations, i.e. modulo operations. Modulo operations are well known to one of ordinary skill in the art. Thus, such operations will not be described in great detail herein. However, it should be appreciated that a RNS residue representation for some weighted value “a” can be defined by mathematical Equation (1).
R={a modulo m0, a modulo m1, . . . , a modulo mN-1} (1)
where R is a RNS residue N-tuple value representing a weighted value “a”. Further, R(nT) can be a representation of the RNS solution of a polynomial equation f(x(nT)) defined as R(nT)={f0(x(nT)) modulo m0, f1(x(nT)) modulo m1, . . . , fN-1(x(nT)) modulo mN-1}. m0, m1, . . . , mN-1 respectively are the moduli for RNS arithmetic operations applicable to each polynomial equation f0(x(nT)), . . . , fN-1(x(nT)).
From the foregoing, it will be appreciated that the RNS employed for solving each of the polynomial equations f0(x(nT)), . . . , fN-1(x(nT)) respectively has a selected modulus value m0, m1, . . . , mN-1. The modulus value chosen for each RNS moduli is preferably selected to be relatively prime numbers p0, p1, . . . , pN-1. The phrase “relatively prime numbers” as used herein refers to a collection of natural numbers having no common divisors except one (1). Consequently, each RNS arithmetic operation employed for expressing a solution as an RNS residue value uses a different prime number p0, p1, . . . , pN-1 as a moduli m0, m1, . . . , mN-1.
Those of ordinary skill in the art will appreciate that the RNS residue value calculated as a solution to each one of the polynomial equations f0(x(nT)), . . . , fN-1(x(nT)) will vary depending on the choice of prime numbers p0, p1, . . . , pN-1 selected as a moduli m0, m1, . . . , mN-1. Moreover, the range of values will depend on the choice of relatively prime numbers p0, p1, . . . , pN-1 selected as a moduli m0, m1, . . . , mN-1. For example, if the prime number five hundred three (503) is selected as modulus m0, then an RNS solution for a first polynomial equation f0(x(nT)) will have an integer value between zero (0) and five hundred two (502). Similarly, if the prime number four hundred ninety-one (491) is selected as modulus m1, then the RNS solution for a second polynomial equation f1(x(nT)) has an integer value between zero (0) and four hundred ninety (490).
According to an embodiment of the invention, each of the N polynomial equations f0(x(nT)), . . . , fN-1(x(nT)) is selected as an irreducible cubic polynomial equation having chaotic properties in Galois field arithmetic. Each of the N polynomial equations f0(x(nT)), . . . , fN-1(x(nT)) can also be selected to be a constant or varying function of time. The irreducible cubic polynomial equation is defined by a mathematical Equation (2).
f(x(nT))=Q(k)x3(nT)+R(k)x2(nT)+S(k)x(nT)+C(k,L) (2)
where n is a sample time index value. k is a polynomial time index value. L is a constant component time index value. T is a fixed constant having a value representing a time increment. Q, R, and S are coefficients that define the polynomial equation f(x(nT)). C is a coefficient of x(nT) raised to a zero power and is therefore a constant for each polynomial characteristic. In one embodiment, a value of C is selected which empirically is determined to produce an irreducible form of the stated polynomial equation f(x(nT)) for a particular prime modulus. For a given polynomial with fixed values for Q, R, and S more than one value of C can exist, each providing a unique iterative sequence. Still, the invention is not limited in this regard.
According to another embodiment of the invention, the N polynomial equations f0(x(nT)) . . . fN-1(x(nT)) are identical exclusive of a constant value C. For example, a first polynomial equation f0(x(nT)) is selected as f0(x(nT))=3x3(nT)+3x2(nT)+x(nT)+C0. A second polynomial equation f1(x(nT)) is selected as f1(x(nT))=3x3(nT)+3×(nT)+x(nT)+C1. A third polynomial equation f2(x(nT)) is selected as f2(x(nT))=3x3(nT)+3x2(nT)+x(nT)+C2, and so on. Each of the constant values C0, C1, . . . , CN-1 is selected to produce an irreducible form in a residue ring of the stated polynomial equation f(x(nT))=3x3(nT)+3x2(nT)+x(nT)+C. In this regard, it should be appreciated that each of the constant values C0, C1, . . . , CN-1 is associated with a particular modulus m0, m1, . . . , mN-1 value to be used for RNS arithmetic operations when solving the polynomial equation f(x(nT)). Such constant values C0, C1, . . . , CN-1 and associated modulus m0, m1, . . . , mN-1 values which produce an irreducible form of the stated polynomial equation f(x(nT)) are listed in the following Table (1).
Still, the invention is not limited in this regard.
The number of discrete magnitude states (dynamic range) that can be generated with the system shown in
Referring again to
According to an embodiment of the invention, each binary sequence representing a residue value has a bit length (BL) defined by a mathematical Equation (3).
BL=Ceiling[Log 2(m)] (3)
where m is selected as one of moduli m0, m1, . . . , mN-1. Ceiling[u] refers to a next highest integer with respect to an argument u.
In order to better understand the foregoing concepts, an example is useful. In this example, six (6) relatively prime moduli are used to solve six (6) irreducible polynomial equations f0(x(nT)), . . . , f5(x (nT)). A prime number p0 associated with a first modulus m0 is selected as five hundred three (503). A prime number p1 associated with a second modulus m1 is selected as four hundred ninety one (491). A prime number p2 associated with a third modulus m2 is selected as four hundred seventy-nine (479). A prime number p3 associated with a fourth modulus m3 is selected as four hundred sixty-seven (467). A prime number p4 associated with a fifth modulus m4 is selected as two hundred fifty-seven (257). A prime number p5 associated with a sixth modulus m5 is selected as two hundred fifty-one (251). Possible solutions for f0(x(nT)) are in the range of zero (0) and five hundred two (502) which can be represented in nine (9) binary digits. Possible solutions for f1(x(nT)) are in the range of zero (0) and four hundred ninety (490) which can be represented in nine (9) binary digits. Possible solutions for f2(x(nT)) are in the range of zero (0) and four hundred seventy eight (478) which can be represented in nine (9) binary digits. Possible solutions for f3(x(nT)) are in the range of zero (0) and four hundred sixty six (466) which can be represented in nine (9) binary digits. Possible solutions for f4(x(nT)) are in the range of zero (0) and two hundred fifty six (256) which can be represented in nine (9) binary digits. Possible solutions for f5(x(nT)) are in the range of zero (0) and two hundred fifty (250) which can be represented in eight (8) binary digits. Arithmetic for calculating the recursive solutions for polynomial equations f0(x(nT)), . . . , f4(x (nT)) requires nine (9) bit modulo arithmetic operations. The arithmetic for calculating the recursive solutions for polynomial equation f5(x(nT)) requires eight (8) bit modulo arithmetic operations. In aggregate, the recursive results f0(x(nT)), . . . , f5(x (nT)) represent values in the range from zero (0) to M−1. The value of M is calculated as follows: p0·p1·p2·p3·p4·p5=503·491·479·467·257·251=3,563,762,191,059,523. The binary number system representation of each RNS solution can be computed using Ceiling[Log 2(3,563,762,191,059,523)]=Ceiling[51.66]=52 bits. Because each polynomial is irreducible, all 3,563,762,191,059,523 possible values are computed resulting in a sequence repetition time of M times T seconds, i.e, a sequence repetition times an interval of time between the computation of each values in the sequence of generated values. Still, the invention is not limited in this regard.
Referring again to
In some embodiments of the invention, the RNS solutions Nos. 1 through N are mapped to a weighted number system representation by determining a series of digits in the weighted number system based on the RNS solutions Nos. 1 through N. The term “digit” as used herein refers to a symbol of a combination of symbols to represent a number. For example, a digit can be a particular bit of a binary sequence. In other embodiments of the invention, the RNS solutions Nos. 1 through N are mapped to a weighted number system representation by identifying a number in the weighted number system that is defined by the RNS solutions Nos. 1 through N. According to yet another embodiment of the invention, the RNS solutions Nos. 1 through N are mapped to a weighted number system representation by identifying a truncated portion of a number in the weighted number system that is defined by the RNS solutions Nos. 1 through N. The truncated portion can include any serially arranged set of digits of the number in the weighted number system. The truncated portion can also be exclusive of a most significant digit of the number in the weighted number system. The phrase “truncated portion” as used herein refers to a chaotic sequence with one or more digits removed from its beginning and/or ending. The phrase “truncated portion” also refers to a segment including a defined number of digits extracted from a chaotic sequence. The phrase “truncated portion” also refers to a result of a partial mapping of the RNS solutions Nos. 1 through N to a weighted number system representation.
In some embodiments of the invention, a mixed-radix conversion method is used for mapping RNS solutions Nos. 1 through N to a weighted number system representation. “The mixed-radix conversion procedure to be described here can be implemented in” [modulo moduli only and not modulo the product of moduli.] See Residue Arithmetic and Its Applications To Computer Technology, written by Nicholas S. Szabo & Richard I. Tanaka, McGraw-Hill Book Co., New York, 1967. [In a mixed-radix number system,] “a number x may be expressed in a mixed-radix form:
where the Ri are the radices, the ai are the mixed-radix digits, and 0≦ai<Ri. For a given set of radices, the mixed-radix representation of x is denoted by (an, an-1, . . . , a1) where the digits are listed order of decreasing significance.” See Id. “The multipliers of the digits ai are the mixed-radix weights where the weight of ai is
For conversion from the RNS to a mixed-radix system, a set of moduli are chosen so that mi=Ri. A set of moduli are also chosen so that a mixed-radix system and a RNS are said to be associated. “In this case, the associated systems have the same range of values, that is
The mixed-radix conversion process described here may then be used to convert from the [RNS] to the mixed-radix system.” See Id.
“If mi=Ri, then the mixed-radix expression is of the form:
where ai are the mixed-radix coefficients. The ai are determined sequentially in the following manner, starting with a1.” See Id.
is first taken modulo m1. “Since all terms except the last are multiples of m1, we have xm
“To obtain a2, one first forms x-a1 in its residue code. The quantity x-a1 is obviously divisible by m1. Furthermore, m1 is relatively prime to all other moduli, by definition. Hence, the division remainder zero procedure [Division where the dividend is known to be an integer multiple of the divisor and the divisor is known to be relatively prime to M] can be used to find the residue digits of order 2 through N of
Inspection of
shows then that x is a2. In this way, by successive subtracting and dividing in residue notation, all of the mixed-radix digits may be obtained.” See Id.
“It is interesting to note that
and in general for i>1.”
See Id. From the preceding description it is seen that the mixed-radix conversion process is iterative. The conversion can be modified to yield a truncated result. Still, the invention is not limited in this regard.
In some embodiments of the invention, a Chinese remainder theorem (CRT) arithmetic operation is used to map the RNS solutions Nos. 1 through N to a weighted number system representation. The CRT arithmetic operation can be defined by a mathematical Equation (12).
Equation (12) can be re-written in iterative form as mathematical Equation (12a).
where Y(nT) is the result of the CRT arithmetic operation. n is a sample time index value. T is a fixed constant having a value representing a time interval or increment. x0-xN-1 are RNS solutions Nos. 1 through N. p0, p1, . . . , pN-1 are prime number moduli. M is a fixed constant defined by a product of the relatively prime numbers p0, p1, pN-1. b0, b1, . . . , bN-1 are fixed constants that are chosen as the multiplicative inverses of the product of all other primes modulo p0, p1, . . . , pN-1, respectively. Equivalently,
The bj's enable an isomorphic and equal mapping between an RNS N-tuple value representing a weighted number and said weighted number. However without loss of chaotic properties, the mapping need only be unique and isomorphic. As such, a weighted number x can map into a tuple y. The tuple y can map into a weighted number z. The weighted number x is not equal to x as long as all tuples map into unique values for z in a range from zero (0) to M−1. Therefore, in some embodiments of the invention, the bj's can be defined as
In other embodiments of the invention, all bj's can be set equal to one or more values without loss of the chaotic properties. Different values of bj apply a bijective mapping within the RNS, but do not interfere with the CRT combination process.
The chaotic sequence output Y(nT) can be expressed in a binary number system representation. As such, the chaotic sequence output Y(nT) can be represented as a binary sequence. Each bit of the binary sequence has a zero (0) value or a one (1) value. The chaotic sequence output Y(nT) can have a maximum bit length (MBL) defined by a mathematical Equation (15).
MBL=Ceiling[Log 2(M)] (15)
where M is the product of the relatively prime numbers p0, p1, pN-1 selected as moduli m0, m1, . . . , mN-1. In this regard, it should be appreciated the M represents a dynamic range of a CRT arithmetic operation. The phrase “dynamic range” as used herein refers to a maximum possible range of outcome values of a CRT arithmetic operation. Accordingly, the CRT arithmetic operation generates a chaotic numerical sequence with a periodicity equal to the inverse of the dynamic range M. The dynamic range requires a Ceiling[Log 2(M)] bit precision.
In some embodiments of the invention, M equals three quadrillion five hundred sixty-three trillion seven hundred sixty-two billion one hundred ninety-one million fifty-nine thousand five hundred twenty-three (3,563,762,191,059,523). By substituting the value of M into Equation (6), the bit length (BL) for a chaotic sequence output Y expressed in a binary system representation can be calculated as follows: BL=Ceiling/Log 2(3,563,762,191,059,523)=52 bits. As such, the chaotic sequence output Y(nT) is a fifty-two (52) bit binary sequence having an integer value between zero (0) and three quadrillion five hundred sixty-three trillion seven hundred sixty-two billion one hundred ninety-one million fifty-nine thousand five hundred twenty-two (3,563,762,191,059,522), inclusive. Still, the invention is not limited in this regard. For example, the chaotic sequence output Y(nT) can be a binary sequence representing a truncated portion of a value between zero (0) and M−1. In such a scenario, the chaotic sequence output Y(nT) can have a bit length less than Ceiling[Log 2(M)]. It should be noted that while truncation affects the dynamic range of the system it has no effect on the periodicity of a generated sequence.
As one of ordinary skill in art will recognize, the above-described chaotic sequence generation can be iteratively performed. In such a scenario, a feedback mechanism (e.g., a feedback loop) can be provided so that a variable “x” of a polynomial equation can be selectively defined as a solution computed in a previous iteration. Mathematical Equation (2) can be rewritten in a general iterative form: f(x(nT)=Q(k)x3((n−1)T)+R(k)x2((n−1)T)+S(k)x((n−1)T)+C(k,L). For example, a fixed coefficient polynomial equation is selected as f(x(n·1 ms))=3x3((n−1)·1 ms)+3x2((n−1)·1 ms)+x((n−1)·1 ms)+8 modulo 503. n is a variable having a value defined by an iteration being performed. x is a variable having a value allowable in a residue ring. In a first iteration, n equals one (1) and x is selected as two (2) which is allowable in a residue ring. By substituting the value of n and x into the stated polynomial equation f(x(nT)), a first solution having a value forty-six one (46) is obtained. In a second iteration, n is incremented by one and x equals the value of the first solution, i.e., forty-six (46) resulting in the solution 298, 410 mod 503 or one hundred thirty-one (131). In a third iteration, n is again incremented by one and x equals the value of the second solution.
Referring now to
As shown in
After step 210, the method 200 continues with step 212. In step 212, a value for time increment “T” is selected. Thereafter, an initial value for “x” is selected. In this regard, it should be appreciated that the initial value for “x” can be any value allowable in a residue ring. Subsequently, step 216 is performed where RNS arithmetic operations are used to iteratively determine RNS solutions for each of the stated polynomial equations f0(x(nT)), . . . , fN-1(x(nT)). In step 218, a series of digits in a weighted number system are determined based in the RNS solutions. This step can involve performing a mixed radix arithmetic operation or a CRT arithmetic operation using the RNS solutions to obtain a chaotic sequence output.
After step 218, the method 200 continues with a decision step 220. If a chaos generator is not terminated (220:NO), then step 224 is performed where a value of “x” in each polynomial equation f0(x(nT)), . . . , fN-1(x(nT)) is set equal to the RNS solution computed for the respective polynomial equation f0(x(nT)), . . . , fN-1(x(nT)) in step 216. Subsequently, the method 200 returns to step 216. If the chaos generator is terminated (220:YES), then step 222 is performed where the method 200 ends.
One of ordinary skill in the art will appreciate that the method 200 is only one exemplary method for generating a chaotic sequence. However, the invention is not limited in this regard and any other method for generating a chaotic sequence can be used without limitation.
Referring now to
Referring again to
Each of the solutions can be expressed as a unique residue number system (RNS) N-tuple representation. In this regard, it should be appreciated that the computing processors 3020-302N-1 employ modulo operations to calculate a respective solution for each polynomial equation f0(x(nT)), . . . , fN-1(x(nT)) using modulo based arithmetic operations. Each of the computing processors 3020-302N-1 are comprised of hardware and/or software configured to utilize a different relatively prime number p0, p1, . . . , pN-1 as a moduli m0, m1, . . . , mN-1 for modulo based arithmetic operations. The computing processors 3020-302N-1 are also comprised of hardware and/or software configured to utilize modulus m0, m1, . . . , mN-1 selected for each polynomial equation f0(x(nT)), . . . , fN-1(x(nT)) so that each polynomial equation f0(x(nT)), . . . , fN-1(x(nT)) is irreducible. The computing processors 3020-302N-1 are further comprised of hardware and/or software configured to utilize moduli m0, m1, . . . , mN-1 selected for each polynomial equation f0(x(nT)), . . . , fN-1(x(nT)) so that solutions iteratively computed via a feedback mechanism 3100-310N-1 are chaotic. In this regard, it should be appreciated that the feedback mechanisms 3100-310N-1 are provided so that the solutions for each polynomial equation f0(x(nT)), . . . , fN-1(x(nT)) can be iteratively computed. Accordingly, the feedback mechanisms 3100-310N-1 are comprised of hardware and/or software configured to selectively define a variable “x” of a polynomial equation as a solution computed in a previous iteration.
Referring again to
According to an embodiment of the invention, the computing processors 3020-302N-1 are further comprised of memory based tables (not shown) containing pre-computed residue values in a binary number system representation. The address space of each memory table is at least from zero (0) to mm−1 for all m, m0 through mN-1. On each iteration, the table address is used to initiate the sequence. Still, the invention is not limited in this regard.
Referring again to
In the various embodiments of the invention, the mapping processor 304 can be comprised of hardware and/or software configured to identify a truncated portion of a number in the weighted number system that is defined by the moduli solutions Nos. 1 through N. For example, the mapping processor 304 can also be comprised of hardware and/or software configured to select the truncated portion to include any serially arranged set of digits of the number in the weighted number system. Further, the mapping processor 304 can include hardware and/or software configured to select the truncated portion to be exclusive of a most significant digit when all possible weighted numbers represented by P bits are not mapped, i.e., when M−1<2P. P is a fewest number of bits required to achieve a binary representation of the weighted numbers. Still, the invention is not limited in this regard.
Referring again to
One of ordinary skill in the art will appreciate that the chaotic generator 300 shown in
Spread Spectrum Communications with Chaotic Sequences
As described above, another aspect of the invention provides for using a communication system disclosed that utilizes a spread spectrum communications system using chaotic sequences, hereinafter a coherent chaotic sequence spread spectrum (CCSSS) method. That is, prior to being transmitted, symbols in a data signal are combined with a higher rate chaotic sequence (analogous to the binary PN spreading sequence known as a chipping code in conventional direct sequence spread spectrum systems) that spreads the spectrum of the data according to a spreading ratio. The resulting signal resembles a truly random signal, but this randomness can be deciphered at the receiving end to recover the original data. In particular, the data signal is recovered by despreading the received signal using the same chaotic sequence which is generated coherently at a receiver. The CCSSS system in relation to
Referring now to
The receiver 404 is configured to receive transmitted analog chaotic signals 406 from the transmitter 402. The receiver 404 is also configured to down convert, digitize, and de-spread the analog chaotic signals 406 by correlating it with a replica of the chaotic sequence generated at the transmitter 402. The chaotic sequence is also time synchronized to the analog chaotic signal 406: i.e., a sampling rate of the chaotic sequence used in the receiver is synchronized with a clock (not shown) of the transmitter 402. The output of the arithmetic operation that de-spreads the analog chaotic signal 406 is hereinafter referred to as a de-spread signal. In this regard, it should be understood that the receiver 404 is further configured to process a de-spread signal for obtaining data contained therein. The receiver 404 is configured to convert the data into text, sound, pictures, navigational-position information, and/or any other type of useful payload information that can be communicated. The receiver 404 is described in greater detail below in relation to
Referring now to
Referring again to
Referring again to
The symbol data formatter 506 is configured to process bits of data for forming channel encoded symbols. In one embodiment of the invention, the source encoded symbols are phase shift keyed (PSK) encoded. If it is desired to use a non-coherent form of PSK with the coherent chaos spread spectrum system, then the symbol data formatter 506 can also be configured to differentially encode formed PSK symbol data words. Differential encoding is well known to one of ordinary skill in the art and therefore will not be described in great detail herein. The symbol data formatter 506 can be further configured to communicate non-differentially encoded PSK symbol data words and/or differentially encoded PSK symbol data words to the multiplexer 514. Still, the invention is not limited in this regard.
In one embodiment of the invention, the symbol data formatter 506 is functionally similar to a serial in/parallel out shift register where the number of parallel bits out is equal to log base two (log2) of the order of the channel encoder 516. In this regard, the symbol data formatter 506 is selected for use with a quadrature phase shift keying (QPSK) channel encoder. As such, the symbol data formatter 506 is configured to perform a QPSK formatting function for grouping two (2) bits of data together to form a QPSK symbol data word (i.e., a single two bit parallel word). Thereafter, the symbol data formatter 506 communicates the symbol data word to the multiplexer 514. Still, the invention is not limited in this regard.
In another embodiment of the invention, the symbol data formatter 506 is functionally similar to a serial in/parallel out shift register where the number of parallel bits out is equal to log base two (log2) of the order of the channel encoder 516. In this regard, the symbol data formatter 506 is selected for use with a binary phase shift keying (BPSK) channel encoder. As such, the symbol data formatter 506 is configured to map one bit of data per symbol time to a BPSK channel encoder. Thereafter, the symbol data formatter 506 communicates the BPSK symbol data word to the multiplexer 514. Still, the invention is not limited in this regard.
In still another embodiment of the invention, the symbol data formatter 506 is selected for use with a sixteen quadrature amplitude modulation (16 QAM) modulator. As such, the symbol data formatter 506 is configured to map four (4) bits to a 16 QAM symbol data word. Thereafter, the symbol data formatter 506 communicates the 16 QAM symbol data word to the multiplexer 514. Still, the invention is not limited in this regard.
In yet another embodiment of the invention, the symbol data formatter 506 is selected for use with a binary amplitude shift keying (ASK) modulator. As such, the symbol data formatter 506 is configured to map one bit of data to a ASK symbol data word. Thereafter, the symbol data formatter 506 communicates the ASK symbol data word to the multiplexer 514. Still, the invention is not limited in this regard.
The transmitter 402 also includes an acquisition data generator 508 capable of generating a “known data preamble” that can be used to enable initial synchronization of a chaotic sequence generated in the transmitter 402 and the receiver 404. The duration of this “known data preamble” is determined by an amount required by the receiver 404 to synchronize with the transmitter 402 under known worst case channel conditions. In some embodiments of the invention, the “known data preamble” is a repetition of the same known symbol. In other embodiments of the invention, the “known data preamble” is a series of known symbols. The acquisition data generator 508 can be further configured to communicate the “known data preamble” to the multiplexer 514.
Referring again to
In some embodiments of the invention, the “known data preamble” is stored in a modulated form. In such embodiments, the architecture of
According to another embodiment of the invention, the “known data preamble” may be injected at known intervals to aid in periodic resynchronization of the chaotic sequence generated in the transmitter 402 and the receiver 404. This would typically be the case for an implementation meant to operate in harsh channel conditions. Still, the invention is not limited in this regard.
Referring again to
Referring again to
According to an embodiment of the invention, the transmitter 402 is further comprised of a sample rate matching device (not shown) between the channel encoder 516 and the digital complex multiplier 524. The sample rate matching device (not shown) is provided for holding the amplitude-and-time-discrete digital signal for a duration compatible with the chaos sampling rate. As should be appreciated, the sample rate matching device (not shown) performs sample duration matching on the amplitude-and-time-discrete digital signal so that a sample duration of the amplitude-and-time-discrete digital signal is consistent with a digital chaotic sequence communicated to the digital complex multiplier 524. Still, the invention is not limited in this regard.
Referring again to
The rate at which the digital chaotic sequence is generated is an integer multiple of an information symbol rate. The greater the ratio between the information symbol period and the sample period of the digital chaotic sequence, the higher a spreading gain. The chaos generator 300 communicates the chaotic sequence to a RUQG 520. The RUQG 520 is configured to statistically transform a digital chaotic sequence into a transformed digital chaotic sequence with pre-determined statistical properties. The transformed digital chaotic sequence can have a characteristic form including combinations of real, complex, or quadrature, being of different word widths, and having different statistical distributions. For example, the RUQG 520 may take in two (2) uniformly distributed real inputs from the chaos generator 300 and convert those via a complex-valued bivariate Box-Muller transformation to a quadrature output having statistical characteristics of a Gaussian distribution. Such conversions are well understood by one of ordinary skill in the art, and therefore will not be described in great detail herein. However, it should be understood that such techniques may use nonlinear processors, look-up tables, iterative processing (CORDIC functions), or other similar mathematical processes. The RUQG 520 is further configured to communicate transformed chaotic sequences to the SRCF 522.
The statistically transformed output of the digital chaotic sequence has a multi-bit resolution consistent with a resolution of the DAC 532. The RUQG 520 communicates the statistically transformed output of the digital chaotic sequence to the SRCF 522. For example, the RUQG 520 communicates an in-phase (“I”) data and quadrature phase (“Q”) data to the SRCF 522 when the channel encoder 516 is configured to yield a complex output representation. Still, the invention is not limited in this regard.
If the chaos sample rate of the transformed chaotic sequence is different than the sample rate required by subsequent signal processing, then the two rates must be matched. The chaotic sequence can therefore be resampled in the SRCF 522. For example, SRCF 522 can be comprised of a real interpolation filters to upsample each of the in-phase and quadrature-phase processing paths of the chaotic sequence. As should be appreciated, the SRCF 522 performs a sample rate change on the transformed digital chaotic sequence so that a sample rate of the transformed digital chaotic sequence is the same as the sampling rates required by subsequent signal processing operations. The SRCF 522 is also configured to communicate a resampled, transformed digital chaotic sequence to the digital complex multiplier 524.
According to an embodiment of the invention, the RUQG 520 statistically transforms a digital chaotic sequence into a quadrature Gaussian form of the digital chaotic sequence. This statistical transformation is achieved via a nonlinear processor that combines lookup tables and embedded computational logic to implement the conversion of two (2) independent uniformly distributed random variables into a quadrature pair of Gaussian distributed variables. One such structure for this conversion is as shown in the mathematical expressions (16) and (17).
G1=√{square root over (−2 log(u1))}·cos(2πu2) (16)
G2=√{square root over (−2 log(u1))}·sin(2πu2) (17)
where {u1, u2} are uniformly distributed independent input random variables and {G1, G2} are Gaussian distributed output random variables. In such a scenario, the SRCF 522 is comprised of one sample rate change filter to resample an in-phase (“I”) data sequence and a second sample rate change filter to resample a quadrature-phase (“Q”) data sequence. The SRCF 522 is configured to communicate a resampled, transformed digital chaotic sequence to the digital complex multiplier 524. More particularly, the SRCF 522 communicates an in-phase (“I”) data and quadrature phase (“Q”) data to the digital complex multiplier 524. Still, the invention is not limited in this regard.
The digital complex multiplier 524 performs a complex multiplication on the digital chaotic sequence output from the SRCF 522 and the amplitude-and-time-discrete digital signal output from the channel encoder 516. The resulting output is a digital representation of a chaotic sequence spread spectrum modulated IF signal in which the digital data from the channel encoder 516 has been spread over a wide frequency bandwidth in accordance with a chaotic sequence generated by the chaos generator 300.
The digital complex multiplier 524 is configured to combine a digital chaotic sequence with an amplitude-and-time-discrete digital signal using an arithmetic operation. The arithmetic operation is selected as a complex-valued digital multiplication operation. The complex-valued digital multiplication operation includes multiplying the amplitude-and-time-discrete digital signal by the digital chaotic sequence to obtain a digital chaotic output signal. The digital complex multiplier 524 is also configured to communicate digital chaotic output signals to the interpolator 526.
The interpolator 526, real part of complex multiplier 528 and quadrature digital local oscillator 530 operate in tandem to form an intermediate frequency (IF) translator which frequency modulates a quadrature first intermediate frequency (IF) signal received from the complex multiplier to a second real intermediate frequency (IF) signal. Such digital intermediate frequency (IF) translators are known to one of ordinary skill in the art and shall not be discussed in detail here.
The interpolator 526 accepts an input from the complex multiplier 524. In one embodiment the modulated symbols are in quadrature form and the interpolator is implemented as two real interpolators. Still, the invention is not limited in this regard.
The interpolator 526 raises the sample rate of the amplitude-and-time-discrete digital signal received from the complex multiplier 524 to a rate compatible with the bandwidth and center frequency of the second IF. The digital local oscillator 530 generates a complex quadrature amplitude-and-time-discrete digital sinusoid at a frequency which shall translate the first intermediate frequency (IF) to a desired second intermediate frequency (IF). The digital local oscillator 530 is also configured to pass its output to the real part of complex multiplier 528.
The real part of complex multiplier 528 is configured to accept as its inputs the quadrature output of the interpolator 528 and the quadrature output of the digital local oscillator 530. The real part of a complex multiplication is passed so that the real part of complex multiplier 528 implements only the real output portion of a complex multiplication. The real part of complex multiplier 528 is configured to pass its output to the DAC 532. Still, the invention is not limited in this regard.
In some embodiments of the invention, the digital chaotic sequence and the amplitude-and-time-discrete digital signal are zero intermediate frequency (IF) signals. The digital chaotic sequence is used to amplitude modulate the “known data preamble” and the information symbols via an efficient instantiation of a complex multiplier. The result of this amplitude modulation process is a zero IF signal. Still, the invention is not limited in this regard.
Referring again to
In some applications, it can be desirable to change a sampling rate at the output of the digital complex multiplier 524 only, for example when using an interpolating DAC. An IF translator consisting of an interpolator 526 only can be provided for this purpose.
Referring again to
It should be understood that the digital generation of the digital chaotic sequence at the transmitter 402 and receiver 404 is kept closely coordinated under the control of a precision real time reference 512 clock. The higher the precision of the clock 512, the closer the synchronization of the chaos generator 300 of the transmitter 402 and the chaos generator (described below in relation to
Referring again to
One of ordinary skill in the art will appreciate that the transmitter 402, as shown in
Referring now to
Referring again to
Referring again to
The RF to IF conversion device 610 is configured to mix the analog input signal to a preferred IF for conversion to a digital signal at the A/D converter 614. The RF to IF conversion device 610 is also configured to communicate a mixed analog input signal to the anti-alias filter 612. The anti-alias filter 612 is configured to restrict a bandwidth of a mixed analog input signal. The anti-alias filter 612 is also configured to communicate a filtered, analog input signal to the A/D converter 614. The A/D converter 614 is configured to convert a received analog input signal to a digital signal. The A/D converter 614 is also configured to communicate a digital input signal to a second IF translator which is comprised of quadrature fixed digital local oscillator 660, the real multipliers 616, 618, the low pass filters 662, 664, the complex multiplier 666, and the programmable quadrature digital local oscillator 622.
The multiplier 616 is configured to receive a digital word as input from the A/D converter 614 and a digital word from the in-phase component of the quadrature fixed digital local oscillator 660. The multiplier 616 multiplies the output of the A/D converter 614 by the in-phase component of the quadrature digital local oscillator 660. The multiplier 616 is also configured to communicate a digital output word. The multiplier 618 is configured to receive a digital word as input from the A/D converter 614 and a digital word from the quadrature-phase component of the quadrature fixed digital local oscillator 660. The multiplier 618 multiplies the output of the A/D converter 614 by the quadrature-phase component of the quadrature fixed digital local oscillator 660. The multiplier 618 is also configured to communicate a digital output word. The quadrature fixed digital local oscillator generates a fixed frequency quadrature signal used to mix the output of the A/D converter 614 to an approximately zero intermediate frequency (IF).
The low pass filter 662 low pass filters the baseband output of multiplier 616. The low pass filter 662 is also configured to communicate a digital output word. The low pass filter 664 low pass filters the baseband output of multiplier 618. The low pass filter 664 is also configured to communicate a digital output word. The output of low pass filters 662, 664 is collectively a quadrature approximate baseband IF signal. The complex multiplier 666 is configured to receive a digital word as input from the low pass filter 662, a digital word as input from the low pass filter 664, a digital word from the in-phase component of the quadrature digital local oscillator 622, and a digital word from the quadrature-phase component of the quadrature digital local oscillator 622. The complex multiplier 666 multiplies the output of the low pass filters 662,664 by the quadrature fine tuning signal of the quadrature digital local oscillator 622. The complex multiplier 666 is also configured to communicate a digital output word.
The quadrature digital local oscillator 622 generates a complex quadrature amplitude-and-time-discrete digital sinusoid at a frequency which shall remove detected frequency and phase offsets in the quadrature baseband IF signal. The quadrature digital local oscillator accepts as its inputs a binary phase control word and a binary frequency control word from the loop control circuit 620. Quadrature digital local oscillators are known to one of ordinary skill in the art, and therefore will not be described in detail herein.
The IF translator is configured to mix the digital input signal to a preferred IF for processing at the correlator 628 and the digital complex multiplier 624. The IF translator is also configured to communicate a digital input signal to the correlator 628 and the digital complex multiplier 624. As will be appreciated by one of ordinary skill in the art, the output of the IF translator can include an in-phase (“I”) data and quadrature phase (“Q”) data. As such, the IF translator can communicate I and Q data to the correlator 628 and the digital complex multiplier 624.
The digital complex multiplier 624 is configured to perform a complex multiplication in the digital domain. In the complex-valued digital multiplier 624, the digital input signal from the IF translator is multiplied by a digital representation of a chaotic sequence. The chaotic sequence is generated in the chaos generator 300, as described with reference to
The RUQG 642 is configured to statistically transform a digital chaotic sequence into a transformed digital chaotic sequence. The transformed digital chaotic sequence can have a characteristic form including combinations of real, complex, or quadrature, being of different word widths, and having different statistical distributions. One such statistical transformation used in the preferred embodiment is a bivariate Gaussian distribution that converts two (2) independent uniformly distributed random variables to a pair of quadrature Gaussian distributed variables. The RUQG 642 is further configured to communicate transformed chaotic sequences to the re-sampling filter 644.
According to the embodiment of the invention, the RUQG 642 statistically transforms a digital chaotic sequence into a quadrature Gaussian form of the digital chaotic sequence. The RUQG 642 communicates the quadrature Gaussian form of the digital chaotic sequence to the re-sampling filter 644. More particularly, the RUQG 642 communicates an in-phase (“I”) data and quadrature phase (“Q”) data to the re-sampling filter 644. Still, the invention is not limited in this regard.
The re-sampling filter 644 is also configured to forward a transformed chaotic sequence to the digital complex multiplier 624. The re-sampling filter 644 is configured as a sample rate change filter for making the chaos sample rate compatible with the received signal sample rate when the receiver 404 is in acquisition mode. The re-sampling filter 644 is also configured to compensate for transmit and receive clock offsets with less than a certain level of distortion when the receiver is in a steady state demodulation mode. In this regard, it should be appreciated that the re-sampling filter 644 is configured to convert a sampling rate of in-phase (“I”) and quadrature-phase (“Q”) data sequences from a first sampling rate to a second sampling rate without changing the spectrum of the data contained in therein. The re-sampling filter 644 is further configured to communicate in-phase (“I”) and quadrature-phase (“Q”) data sequences to the digital complex multipliers 624, 652, and the multiplexers 646, 648.
It should be noted that if a sampled form of a chaotic sequence is thought of as discrete samples of a continuous band limited chaos then the re-sampling filter 644 is effectively tracking the discrete time samples, computing a continuous representation of the chaotic sequence, and resampling the chaotic sequence at the discrete time points required to match the discrete time points sampled by the A/D converter 614. In effect, input values and output values of the re-sampling filter 644 are not exactly the same because the values are samples of the same waveform taken at slightly offset times. However, the values are samples of the same waveform so the values have the same power spectral density.
Referring again to
The correlator 628 is configured to correlate a chaotic sequence with a digital input signal. In this regard, it should be understood that, the sense of the real and imaginary components of the correlation is directly related to the values of the real and imaginary components of the symbols of a digital input signal. It should also be understood that in some embodiments, the sense of the real and imaginary components of the correlation is directly related to the values of the real and imaginary components of the PSK symbols of a digital input signal. Thus, when the correlator 628 is in a steady state demodulation mode the output of the correlator 628 is PSK symbol soft decisions. In this regard, it should be appreciated that soft information refers to soft-values (which are represented by soft-decision bits) that comprise information about the bits contained in a sequence. In particular, soft-values are values that represent the probability that a particular bit in a sequence is either a one (1) or a zero (0). For example, a soft-value for a particular bit can indicate that a probability of a bit being a one (1) is p(1)=0.3. Conversely, the same bit can have a probability of being a zero (0) which is p(0)=0.7.
The correlator 628 is also configured to communicate PSK soft decisions to the hard decision device 630 for final symbol decision making or to the source decoder 634 (path not shown). The hard decision device 630 is configured to communicate symbol decisions to the S/B converter 632. The S/B converter 632 is configured to convert symbols to a binary form. The S/B converter 632 is configured to communicate a binary data sequence to the source decoder 634. The source decoder 634 is configured to decode FEC applied at the transmitter and to pass the decoded bit stream to one or more external devices (not shown) utilizing the decoded data.
The correlator 628 is also configured to acquire initial timing information associated with a chaotic sequence, initial timing associated with a data sequence and to track phase and frequency offset information between the chaotic sequence and a digital input signal. The correlator 628 is also configured to track input signal magnitude information between the chaotic sequence and a digital input signal. Acquisition of initial timing information and tracking of input signal magnitude, phase and frequency offset information are all standard functions in digital communication systems. As such, methods for acquiring initial timing information and tracking phase and frequency offset information are well known to one of ordinary skill in the art, and therefore will not be described in detail herein. However, it should be appreciated that any such method can be used without limitation.
Referring again to
It should be understood that the digital generation of the digital chaotic sequence at the transmitter 402 and receiver 404 is kept closely coordinated under the control of a precision real time reference clock 636. The higher the precision of the clock 636, the closer the synchronization of the chaos generator 300 of the transmitter 402 and the chaos generator 300 of the receiver 404 shall be excluding the effects of processing delay differences and channel propagation times. It is the use of digital chaos generators 300 in the transmitter and receiver that allow the states of the chaos generators to be easily controlled with precision, thus allowing coherent communication.
Referring again to
The operation of the receiver 404 will now be briefly described with regard to an acquisition mode and a steady state demodulation mode.
Acquisition Mode:
In acquisition mode, the re-sampling filter 644 performs a rational rate change and forwards a transformed chaotic sequence to the digital complex multiplier 652. The CEADG 650 generates a modulated acquisition sequence and forwards the same to the digital complex multiplier 652. The digital complex multiplier 652 performs a complex multiplication in the digital domain. In the digital complex multiplier 652, a modulated acquisition sequence from the CEADG 650 is multiplied by a digital representation of a chaotic sequence to yield a reference for a digital input signal that was generated at the transmitter 402 to facilitate initial acquisition. The chaotic sequence is generated in the chaos generator 300. The digital complex multiplier 652 communicates a reference signal to the multiplexers 646, 648. The multiplexers 646, 648 route the reference signal to the correlator 628. The correlator 628 is transitioned into a search mode. In this search mode, the correlator 628 searches across an uncertainty window to locate a received signal state so that the chaos generator 300 can be set with the time synchronized state vector.
Steady State Demodulation Mode:
In steady state demodulation mode, the correlator 628 tracks the correlation between the received modulated signal and the locally generated chaos close to the nominal correlation peak to generate magnitude and phase information as a function of time. This information is passed to the loop control circuit 620. The loop control circuit 620 applies appropriate algorithmic processing to this information to extract phase offset, frequency offset, and magnitude compensation information. The correlator 628 also passes its output information, based on correlation times terminated by symbol boundaries, to the hard decision block 630. The hard decision block 630 compares the correlation information to pre-determined thresholds to make hard symbol decisions. The loop control circuit 620 monitors the output of the correlator 618. When the loop control circuit 620 detects fixed correlation phase offsets, the phase control of the quadrature digital local oscillator 622 is modified to remove the phase offset. When the loop control circuit 620 detects phase offsets that change as a function of time, it adjusts the re-sampling filter 644 which acts as an incommensurate re-sampler when the receiver 404 is in steady state demodulation mode or the frequency control of the quadrature digital local oscillator 622 is modified to remove frequency or timing offsets. When the correlator's 628 output indicates that the received digital input signal timing has “drifted” more than plus or minus a half (½) of a sample time relative to a locally generated chaotic sequence; the loop control circuit 620: (1) adjusts a correlation window in an appropriate temporal direction by one sample time; (2) advances or retards a state of the local chaos generator 300 by one iteration state; and (3) adjusts the re-sampling filter 644 to compensate for the time discontinuity. This loop control circuit 620 process keeps the chaos generator 300 of the transmitter 402 and the chaos generator 300 of the receiver 404 synchronized to within half (½) of a sample time with the advance/retard control.
More precise temporal synchronization is achieved by the resampling filter 644 which can be implemented as a member of the class of polyphase fractional time delay filters. This class of filters is well known to one of ordinary skill in the art, and therefore will not be described in great detail herein.
In this steady state demodulation mode, the symbol timing recovery circuit 626 communicates a symbol onset timing to the correlator 628 for controlling an initiation of a symbol correlation. The correlator 628 correlates a locally generated chaotic sequence with a received digital input signal during a symbol duration. In this regard, it should be understood that the sense and magnitude of a real and imaginary components of the correlation is directly related to the values of the real and imaginary components of symbols of a digital input signal. Accordingly, the correlator 628 generates symbol soft decisions. The correlator 628 communicates the symbol soft decisions to the hard decision device 630 for final symbol decision making. The hard decision device 630 determines symbols using the symbol soft decisions. Thereafter, the hard decision device 630 communicates the symbols to the S/B converter 632. The S/B converter 632 converts the symbol decisions to a binary form. The S/B converter 632 is configured to communicate a binary data sequence to the source decoder 634. The source decoder 634 is configured to decode the FEC applied at the transmitter 402 and pass the decoded bit stream to one or more external devices (not shown) utilizing the decoded data.
One of ordinary skill in the art will appreciate that the receiver 404, as shown in
Transmitting Constant Energy Symbols for Reduced BER
As previously described, another aspect of the previous invention is providing a varying symbol length to compensate for variation in symbol energy due to modulation of the carrier using chaotic sequences. In chaotic communications, because the values of the chips used during modulation of each of the symbols vary according to a non-stationary chaotic evolution, in both magnitude and phase, the total energy used during a relatively small fixed interval will also be non-stationary; therefore the energy used to transmit each symbol will vary according to the chaotic sequence. This generally results in a non-stationary energy per symbol to noise power ratio that provides non-optimal BER performance due to nonlinearities in BER curves. Statistical evaluations of the received SNR result in confidence intervals for a chosen BER performance, leading to higher transmission link margins for the entire transmission.
In the various embodiments of the invention, a novel alternative approach is provided for transmitting data symbols spread with a non-stationary spreading sequence, such as a digitally generated chaotic sequence. In particular, the symbols are processed such that each symbol is transmitted with the same symbol energy. Without altering the non-stationary spreading sequence, the only alternative is to dynamically dither the symbol period (effectively dithering the spreading ratio) such that each symbol has the same amount of transmitted energy. Therefore, in the various embodiments of the invention, symbols are transmitted with varying symbol periods to provide a relatively constant symbol energy that results in an improved BER performance for the transmission. In particular, the various embodiments of the invention provide a varying symbol period for improving BER by evaluating the cumulative amount of symbol energy resulting from chips already used for transmitting a current symbol. The transmitter then only terminates transmission of the current symbol if a minimum threshold symbol energy level is met. In other words, the symbol period for each symbol is extended until the cumulative energy provided by the chips for a current symbol reaches at least a configurable minimum value. In the various embodiments of the invention, such a capability can be provided for CCSSS 400 in several ways. In particular, a computation device can be included in transmitter 402 for making a determination that a next symbol should be transmitted. A similar, if not identical, computation device can be included in receiver 404 (or 690) to similarly determine when to transition receiver processing to the next data symbol.
For example, as shown in
In operation, the computation device 539 obtains a sum of the energy provided by each of the chaotic chips generated and makes a decision as to whether transmission of the current symbol should be continued or terminated (i.e., transmit a next symbol). If the decision is to terminate transmission of the current symbol, the computation device 539 generates a signal (NEXT SYMBOL) to cause the next symbol to be transmitted. For example, as shown in
In addition to ESYM, the computation device 539 can be configured to receive as an input a second threshold value (ENOISE) for use with a selective noise cancellation device (SNCD) within the computation device 539. In such embodiments, the computation device will then include in the total chip sum only chip energy values exceeding a threshold value (ENOISE) to improve SNR. The use of ENOISE and the SNCD will be described below in greater detail.
In another embodiment of the invention, the computation device 539 can be configured (not shown) to communicate a signal (such as NEXT SYMBOL) to the transmitter controller 510 that controls all transmission processes. However, it should be appreciated that any such instantiation of the symbol clock can be used without limitation.
In
Therefore, as shown in
In some embodiments, a selective noise cancellation device 710 is provided. In such embodiments, the input ENOISE threshold parameter is provided to the device. If the energy from a chip as calculated in complex multiplier 704 is less than the value ENOISE, the value is zeroed before being passed to the summing device 706, effectively cancelling its contribution to the total symbol energy. This mechanism is provided to discount instantaneous symbol energies that are statistically expected to be below the noise floor of a received signal and thus contribute negatively to a symbol decision.
As previously described, transmitter 402 and receiver 404 need to be synchronized in order to properly decode the chaotic communications signal. Although identically configured chaos generators and real time reference systems can be used to synchronize encoding and decoding, a receiver also needs to include a computation device in order to properly determine the beginning and end of symbols in the data signal.
Referring back to
One of ordinary skill in the art will appreciate that
In light of the foregoing description of the invention, it should be recognized that the invention can be realized in hardware, software, or a combination of hardware and software. A method of generating a chaotic sequence according to the invention can be realized in a centralized fashion in one processing system, or in a distributed fashion where different elements are spread across several interconnected processing systems. Any kind of computer system, or other apparatus adapted for carrying out the methods described herein, is suited. A typical combination of hardware and software could be a general purpose computer processor, with a computer program that, when being loaded and executed, controls the computer processor such that it carries out the methods described herein. Of course, an application specific integrated circuit (ASIC), and/or a field programmable gate array (FPGA) could also be used to achieve a similar result.
The invention can also be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein, and which, when loaded in a computer system, is able to carry out these methods. Computer program or application in the present context means any expression, in any language, code or notation, of a set of instructions intended to cause a system having an information processing capability to perform a particular function either directly or after either or both of the following a) conversion to another language, code or notation; b) reproduction in a different material form. Additionally, the description above is intended by way of example only and is not intended to limit the invention in any way, except as set forth in the following claims.
All of the apparatus, methods and algorithms disclosed and claimed herein can be made and executed without undue experimentation in light of the present disclosure. While the invention has been described in terms of preferred embodiments, it will be apparent to those of ordinary skill in the art that variations may be applied to the apparatus, methods and sequence of steps of the method without departing from the concept, spirit and scope of the invention. More specifically, it will be apparent that certain components may be added to, combined with, or substituted for the components described herein while the same or similar results would be achieved. All such similar substitutes and modifications apparent to one of ordinary skill in the art are deemed to be within the spirit, scope and concept of the invention as defined.
Number | Name | Date | Kind |
---|---|---|---|
3564223 | Harris et al. | Feb 1971 | A |
4095778 | Wing | Jun 1978 | A |
4646326 | Backof, Jr. et al. | Feb 1987 | A |
4703507 | Holden | Oct 1987 | A |
4893316 | Janc et al. | Jan 1990 | A |
5007087 | Bernstein et al. | Apr 1991 | A |
5048086 | Bianco et al. | Sep 1991 | A |
5077793 | Falk et al. | Dec 1991 | A |
5210770 | Rice | May 1993 | A |
5276633 | Fox et al. | Jan 1994 | A |
5297153 | Baggen et al. | Mar 1994 | A |
5297206 | Orton | Mar 1994 | A |
5319735 | Preuss et al. | Jun 1994 | A |
5412687 | Sutton et al. | May 1995 | A |
5596600 | Dimos et al. | Jan 1997 | A |
5598476 | LaBarre et al. | Jan 1997 | A |
5646997 | Barton | Jul 1997 | A |
5677927 | Fullerton et al. | Oct 1997 | A |
5680462 | Miller et al. | Oct 1997 | A |
5757923 | Koopman, Jr. | May 1998 | A |
5811998 | Lundberg et al. | Sep 1998 | A |
5852630 | Langberg et al. | Dec 1998 | A |
5900835 | Stein | May 1999 | A |
5923760 | Abarbanel et al. | Jul 1999 | A |
5924980 | Coetzee | Jul 1999 | A |
5937000 | Lee et al. | Aug 1999 | A |
6014446 | Finkelstein | Jan 2000 | A |
6023612 | Harris et al. | Feb 2000 | A |
6038317 | Magliveras et al. | Mar 2000 | A |
6078611 | La Rosa et al. | Jun 2000 | A |
6141786 | Cox et al. | Oct 2000 | A |
6212239 | Hayes | Apr 2001 | B1 |
6304216 | Gronemeyer | Oct 2001 | B1 |
6304556 | Haas | Oct 2001 | B1 |
6310906 | Abarbanel et al. | Oct 2001 | B1 |
6314187 | Menkhoff et al. | Nov 2001 | B1 |
6331974 | Yang et al. | Dec 2001 | B1 |
6377782 | Bishop et al. | Apr 2002 | B1 |
6473448 | Shono et al. | Oct 2002 | B1 |
6570909 | Kansakoski et al. | May 2003 | B1 |
6614914 | Rhoads et al. | Sep 2003 | B1 |
6665692 | Nieminen | Dec 2003 | B1 |
6732127 | Karp | May 2004 | B2 |
6744893 | Fleming-Dahl | Jun 2004 | B1 |
6754251 | Sriram et al. | Jun 2004 | B1 |
6766345 | Stein et al. | Jul 2004 | B2 |
6842479 | Bottomley | Jan 2005 | B2 |
6842745 | Occhipinti et al. | Jan 2005 | B2 |
6864827 | Tise et al. | Mar 2005 | B1 |
6865218 | Sourour | Mar 2005 | B1 |
6888813 | Kishi | May 2005 | B1 |
6901104 | Du et al. | May 2005 | B1 |
6937568 | Nicholl et al. | Aug 2005 | B1 |
6980656 | Hinton, Sr. et al. | Dec 2005 | B1 |
6980657 | Hinton, Sr. et al. | Dec 2005 | B1 |
6986054 | Kaminaga et al. | Jan 2006 | B2 |
6993016 | Liva et al. | Jan 2006 | B1 |
6999445 | Dmitriev et al. | Feb 2006 | B1 |
7023323 | Nysen | Apr 2006 | B1 |
7027598 | Stojancic et al. | Apr 2006 | B1 |
7035220 | Simcoe | Apr 2006 | B1 |
7069492 | Piret et al. | Jun 2006 | B2 |
7076065 | Sherman et al. | Jul 2006 | B2 |
7078981 | Farag | Jul 2006 | B2 |
7079651 | Den Boer et al. | Jul 2006 | B2 |
7095778 | Okubo et al. | Aug 2006 | B2 |
7133522 | Lambert | Nov 2006 | B2 |
7170997 | Petersen et al. | Jan 2007 | B2 |
7190681 | Wu | Mar 2007 | B1 |
7200225 | Schroeppel | Apr 2007 | B1 |
7233969 | Rawlins et al. | Jun 2007 | B2 |
7233970 | North et al. | Jun 2007 | B2 |
7245723 | Hinton, Sr. et al. | Jul 2007 | B2 |
7269198 | Elliott et al. | Sep 2007 | B1 |
7269258 | Ishihara et al. | Sep 2007 | B2 |
7272168 | Akopian | Sep 2007 | B2 |
7277540 | Shiba et al. | Oct 2007 | B1 |
7286802 | Beyme et al. | Oct 2007 | B2 |
7310309 | Xu | Dec 2007 | B1 |
7349381 | Clark et al. | Mar 2008 | B1 |
7423972 | Shaham et al. | Sep 2008 | B2 |
7529292 | Bultan et al. | May 2009 | B2 |
7643537 | Giallorenzi et al. | Jan 2010 | B1 |
7725114 | Feher | May 2010 | B2 |
7779060 | Kocarev et al. | Aug 2010 | B2 |
7830214 | Han et al. | Nov 2010 | B2 |
7853014 | Blakley et al. | Dec 2010 | B2 |
7929498 | Ozluturk et al. | Apr 2011 | B2 |
7974146 | Barkley | Jul 2011 | B2 |
20010017883 | Tiirola et al. | Aug 2001 | A1 |
20020012403 | McGowan et al. | Jan 2002 | A1 |
20020034191 | Shattil | Mar 2002 | A1 |
20020034215 | Inoue et al. | Mar 2002 | A1 |
20020041623 | Umeno | Apr 2002 | A1 |
20020054682 | Di Bernardo et al. | May 2002 | A1 |
20020094797 | Marshall et al. | Jul 2002 | A1 |
20020099746 | Tie et al. | Jul 2002 | A1 |
20020110182 | Kawai | Aug 2002 | A1 |
20020115461 | Shiraki et al. | Aug 2002 | A1 |
20020122465 | Agee et al. | Sep 2002 | A1 |
20020128007 | Miyatani | Sep 2002 | A1 |
20020172291 | Maggio et al. | Nov 2002 | A1 |
20020174152 | Terasawa et al. | Nov 2002 | A1 |
20020176511 | Fullerton et al. | Nov 2002 | A1 |
20020186750 | Callaway et al. | Dec 2002 | A1 |
20030007639 | Lambert | Jan 2003 | A1 |
20030016691 | Cho | Jan 2003 | A1 |
20030044004 | Blakley et al. | Mar 2003 | A1 |
20030156603 | Rakib et al. | Aug 2003 | A1 |
20030182246 | Johnson et al. | Sep 2003 | A1 |
20030198184 | Huang et al. | Oct 2003 | A1 |
20040001556 | Harrison et al. | Jan 2004 | A1 |
20040059767 | Liardet | Mar 2004 | A1 |
20040092291 | Legnain et al. | May 2004 | A1 |
20040100588 | Hartson et al. | May 2004 | A1 |
20040146095 | Umeno et al. | Jul 2004 | A1 |
20040156427 | Gilhousen et al. | Aug 2004 | A1 |
20040161022 | Glazko et al. | Aug 2004 | A1 |
20040165681 | Mohan | Aug 2004 | A1 |
20040184416 | Woo | Sep 2004 | A1 |
20040196212 | Shimizu | Oct 2004 | A1 |
20040196933 | Shan et al. | Oct 2004 | A1 |
20050004748 | Pinto et al. | Jan 2005 | A1 |
20050021308 | Tse et al. | Jan 2005 | A1 |
20050031120 | Samid | Feb 2005 | A1 |
20050050121 | Klein et al. | Mar 2005 | A1 |
20050075995 | Stewart et al. | Apr 2005 | A1 |
20050089169 | Kim et al. | Apr 2005 | A1 |
20050129096 | Zhengdi et al. | Jun 2005 | A1 |
20050207574 | Pitz et al. | Sep 2005 | A1 |
20050249271 | Lau et al. | Nov 2005 | A1 |
20050259723 | Blanchard | Nov 2005 | A1 |
20050265430 | Ozluturk et al. | Dec 2005 | A1 |
20050274807 | Barrus et al. | Dec 2005 | A1 |
20060072754 | Hinton et al. | Apr 2006 | A1 |
20060088081 | Withington et al. | Apr 2006 | A1 |
20060123325 | Wilson et al. | Jun 2006 | A1 |
20060209926 | Umeno et al. | Sep 2006 | A1 |
20060209932 | Khandekar et al. | Sep 2006 | A1 |
20060239334 | Kwon et al. | Oct 2006 | A1 |
20060251250 | Ruggiero et al. | Nov 2006 | A1 |
20060264183 | Chen et al. | Nov 2006 | A1 |
20070098054 | Umeno | May 2007 | A1 |
20070121945 | Han et al. | May 2007 | A1 |
20070133495 | Lee et al. | Jun 2007 | A1 |
20070149232 | Koslar | Jun 2007 | A1 |
20070195860 | Yang et al. | Aug 2007 | A1 |
20070201535 | Ahmed | Aug 2007 | A1 |
20070230701 | Park et al. | Oct 2007 | A1 |
20070253464 | Hori et al. | Nov 2007 | A1 |
20070291833 | Shimanskiy | Dec 2007 | A1 |
20080008320 | Hinton et al. | Jan 2008 | A1 |
20080016431 | Lablans | Jan 2008 | A1 |
20080075195 | Pajukoski et al. | Mar 2008 | A1 |
20080080439 | Aziz et al. | Apr 2008 | A1 |
20080084919 | Kleveland et al. | Apr 2008 | A1 |
20080095215 | McDermott et al. | Apr 2008 | A1 |
20080107268 | Rohde et al. | May 2008 | A1 |
20080198832 | Chester | Aug 2008 | A1 |
20080204306 | Shirakawa | Aug 2008 | A1 |
20080263119 | Chester et al. | Oct 2008 | A1 |
20080294707 | Suzuki et al. | Nov 2008 | A1 |
20080294710 | Michaels | Nov 2008 | A1 |
20080294956 | Chester et al. | Nov 2008 | A1 |
20080304553 | Zhao et al. | Dec 2008 | A1 |
20080304666 | Chester et al. | Dec 2008 | A1 |
20080307022 | Michaels et al. | Dec 2008 | A1 |
20080307024 | Michaels et al. | Dec 2008 | A1 |
20090022212 | Ito et al. | Jan 2009 | A1 |
20090034727 | Chester et al. | Feb 2009 | A1 |
20090044080 | Michaels et al. | Feb 2009 | A1 |
20090059882 | Hwang et al. | Mar 2009 | A1 |
20090110197 | Michaels | Apr 2009 | A1 |
20090122926 | Azenkot et al. | May 2009 | A1 |
20090196420 | Chester et al. | Aug 2009 | A1 |
20090202067 | Michaels et al. | Aug 2009 | A1 |
20090245327 | Michaels | Oct 2009 | A1 |
20090279688 | Michaels et al. | Nov 2009 | A1 |
20090279690 | Michaels et al. | Nov 2009 | A1 |
20090285395 | Hu et al. | Nov 2009 | A1 |
20090296860 | Chester et al. | Dec 2009 | A1 |
20090300088 | Michaels et al. | Dec 2009 | A1 |
20090309984 | Bourgain et al. | Dec 2009 | A1 |
20090310650 | Chester et al. | Dec 2009 | A1 |
20090316679 | Van Der Wateren | Dec 2009 | A1 |
20090323766 | Wang et al. | Dec 2009 | A1 |
20090327387 | Michaels et al. | Dec 2009 | A1 |
20100030832 | Mellott | Feb 2010 | A1 |
20100054225 | Hadef et al. | Mar 2010 | A1 |
20100073210 | Bardsley et al. | Mar 2010 | A1 |
20100111296 | Brown et al. | May 2010 | A1 |
20100142593 | Schmid | Jun 2010 | A1 |
20100254430 | Lee et al. | Oct 2010 | A1 |
20100260276 | Orlik et al. | Oct 2010 | A1 |
20110222393 | Kwak et al. | Sep 2011 | A1 |
Number | Date | Country |
---|---|---|
0 849 664 | Jun 1998 | EP |
0 949 563 | Oct 1999 | EP |
2 000 900 | Dec 2008 | EP |
2 000 902 | Dec 2008 | EP |
1167272 | Oct 1969 | GB |
7140983 | Jun 1995 | JP |
2001255817 | Sep 2001 | JP |
2004279784 | Oct 2004 | JP |
2004343509 | Dec 2004 | JP |
2005017612 | Jan 2005 | JP |
WO-0135572 | May 2001 | WO |
WO-2006 110954 | Oct 2006 | WO |
WO 2008 065191 | Jun 2008 | WO |
WO-2008099367 | Aug 2008 | WO |
WO-2008130973 | Oct 2008 | WO |
WO 2009 146283 | Dec 2009 | WO |
Entry |
---|
Aparicio; “Communications Systems Based on Chaos” May 2007. Universidad Rey Juan Carlos. |
Bererber, S.M., et al., “Design of a CDMA System in FPGA Technology”, Vehicular Technology Conference, 2007. VTC2007-SPRING. IEEE 65th Apr. 22, 2007, Apr. 25, 2007, pp. 3061-3065, XP002575053 Dublin ISBN: 1-4244-0266-2 Retrieved from the Internet: URL:http://ieeexplore.ieee.org> [retrieved on Mar. 23, 2010]. |
Desoky, A.H., et al., “Cryptography Software System Using Galois Field Arithmetic” 2006 IEEE Information Assurance Workshop, West Point, NY, Jun. 12-13, Piscataway, NJ, USA IEEE, Jan. 1, 2006, pp. 386-387, XP031099891. |
El-Khamy S E: “New trends in wireless multimedia communications based on chaos and fractals” National Radio Science Conference, 2004. NRSC 2004. Proceedings of the Twenty-First Cairo, Egypt Mar. 16-18, 2004, Piscataway, NJ, USA, IEEE, Mar. 16, 2004, pp. 1-1—1, XP010715117 ISBN: 978-977-5031-77-8. |
Lai, X., et al., “A Proposal for a New Block Encryption Standard” Advances in Cryptology-Eurocrypt '90, Workshop on the Theory and Application of Cryptographic Techniques Proceedings, Springer-Verlag Berlin, Germany, 1998, pp. 389-404, XP000617517. |
Soobul, Y., et al. “Digital chaotic coding and modulation in CDMA” IEEE AFRICON 2002 Oct. 2, 2002,Oct. 4, 2002, pp. 841-846, XP002575052 Retrieved from the Internet: URL:http://ieeexplore.ieee.org> [retrieved on Mar. 23, 2010]. |
Rabiner, Lawrence R., “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition”, Proceedings of the IEEE, vol. 77, No. 2, Feb. 1989. |
Boyar, “Inferring Sequences Produce by Pseudo-Random Number Generators”, Journal of the Associate for Computing Machine, vol. 36, No. 1, pp. 20-41, 1989. |
Barile, M., “Bijective”, From MathWorld—A Wolfram Web Resource, created by Eric W. Weisstein, [online] [retrieved on Nov. 8, 2010] Retrieved from the Internet: <http: / /mathworld.wolfram.com/Bijective.html>. |
Weisstein, E., Surejection:, From MathWorld-AWolfram Web Resource [online] [retrieved on Nov. 8, 2010] Retrieved from the Internet: <http://mathworld.wolfram.com/surjection.html>. |
Weisstein, E., Surejection:, From MathWorld—AWolfram Web Resource [online] [retrieved on Nov. 8, 2010] Retrieved from the Internet: http://mathworld.wolfram.com/injection.html>. |
Harris Corp., International Search Report mailed Feb. 11, 2010, Application Serial No. PCT/US2009/059948. |
Harris Corp., International Search Report mailed Apr. 13, 2010, Application Serial No. PCT/US2009/0069121. |
Harris Corp., International Search Report mailed Apr. 13, 2010, Application Serial No. PCT/US2009/0069118. |
Harris Corp., European Search Report mailed Mar. 4, 2010, Patent Application No. 08009745.4. |
Socek, D., et al., Short Paper: Enhanced 1-D Chaotic Key Based Algorithm for Image Encryption, Sep. 2005, IEEE. |
Abu-Khader, Nabil, Square Root Generator for Galois Field in Multiple-Valued Logic., Recent Patents on Electrical Engineering; Sep. 2011, vol. 4 Issue 3, p. 209-213, 5p, 2 Diagrams, 3 Charts. |
Pirkin, Llya, Calculations in Galois Fields., C/C++ Users Journal; Oct. 2004, vol. 22 Issue 10, p. 14-18, 4p, 1 Color Photograph. |
Popescu, Angel, A Galois Theory for the Field Extension K ((X))/K., Glasgow Mathematical Journal; Sep. 2010, vol. 52 Issue 3, p. 447-451, 5p. |
Pirkin, Ilya, Calculations in Galois Fields., C/C++ Users Journal; Oct. 2004, vol. 22 Issue 10, p. 14-18, 4p, 1 Color Photograph. |
Diaz-Toca, G.M. and Lombardi, H. , Dynamic Galois Theory., Journal of Symbolic Computation; Dec. 2010, vol. 45 Issue 12, p. 1316-1329, 14p. |
Galias, Z., et al., “Quadrature Chaos-Shift Keying: Theory and Performance Analysis”, IEEE Transactions on Circuits and Systems Part I: Regular Papers, IEEE Service Center, New York, NY US, vol. 48, No. 12, Dec. 1, 2001 XP011012427; pp. 1510-1514. |
International Search Report mailed Dec. 30, 2011, European Patent Application No. 11001222.6, in the name of Harris Corporation. |
Abel, et al., “Chaos Communications-Principles, Schemes, and System Analysis” Proceedings for the IEEE, IEEE. New York, NY. vol. 90, No. 5, May 1, 2002, XP011064997, ISSN: 0018-9219. |
Barile, Margherita, “Bijective,” From MathWorld—A Wolfram Web Resource, created by Eric W. Weisstein. http://mathworld.wolfram.com/Bijective.html. |
Chren, W A: “PN Code Generator with Low Delay-power Product for Spread-Spectrum Communication Systems” IEEE Transactions on Circuits and Systems II: Express Briefs, IEEE Service Center, New York, NY US, vol. 46, No. 12, Dec. 1, 1999, pp. 1506-1511, XP000932002, ISSN: 1057-7130. |
De Matteis, A., et al., “Pseudorandom Permutation”. Journal of Computational and Applied Mathematics, Elsevier, Netherlands, vol. 142, No. 2, May 15, 2002, pp. 367-375, XP007906923, ISSN: 0377-0427. |
Deckert, T., et al: “Throughput of WLAN with TDMA and Superimposed Transmission with Resource and Traffic Constraints” Personal, Indoor and Mobile Radio Communications, 2006 IEEE 17th Inter National Symposium on, IEEE, PI, Sep. 1, 2006, pp. 1-5, XP031023581, ISBN: 978-1-4244-0329-5. |
Deckert, T., et al: 1-10 “Superposed Signaling Option for Bandwidth Efficient Wireless LANs” Proceedings of the 7th International Symposium on Wireless Personal Multimedia Communications, [Online] Sep. 15, 2004,XPOO2558039. |
Knuth, D.E., “The Art of Computer Programming, Third Edition; vol. 2 Seminumerical Algorithms”. Feb. 2005, Addison-Wesley, Boston 310200, XP002511903, pp. 142-146, 284-292. |
Knuth, D E: “The Art of Computer Programming, 3.2.2 Other Methods” The Art of Computer Programming. vol. 2: Seminumerical Algorithms, Boston, MA: Addison-Wesley, US, Jan. 1, 1998, pp. 26-40, XP002409615, ISBN: 978-0-0201-89684-8. |
Kolumban, et al., “The Role of Synchronization in Digital Communications Using Chaos—Part II: Chaotic Modulation and Chaotic Synchronization”, IEEE Transactions on Circuits and Systems Part I: Regular Papers, IEEE Service Center, New York, NY US, vol. 45, No. 11, Nov. 1, 1998, XP011011827, ISSN: 1057-7122. |
Kolumban, et al., “Chaotic Communications with Correlator Receivers: Theory and Performance Limits” Proceedings of the IEEE, vol. 90, No. 5, May 2002. |
Leung, et al., “Time-varying synchronization of chaotic systems in the presence of system mismatch” Physical Review E (Statistical, Nonlinear, and Soft Matter Physics) APS through AIP USA, [online] Vo. 69, No. 2, Feb. 1, 2004, pp. 26201-1, XP002499416, ISSN: 1063-651X. Retrieved from the Internet: URL:http://prola.aps.org/pdf/PRE/v69/i2/e026201 [retrieved Oct. 13, 2008]. |
Manikandan, et al, “A Novel Pulse Based Ultrawide Band System Using Chaotic Spreading Sequences” Communication Systems Software and Middleware, 2007. COMSWARE 2007. 2nd International Conference on, IEEE, PI, Jan. 1, 2007, pp. 1-5, XP031113946 ISBN: 978-1-4244-0613-5; p. 1, p. 5. |
Morsche et al., “Signals and Systems,” lecture notes, University of Eindhoven, The Netherlands (1999). |
Nakamura, et al, “Chaotic synchronization-based communications using constant envelope pulse” Electrical Engineering in Japan, [Online] vol. 163, No. 3, Feb. 12, 2008, pp. 47-56, XP002539977 Japan. Retrieved from the Internet: URL:http://www3.interscience.wiley.com/cgi-bin/fulltext/117910986/PDFSTART>; [retrieved on Aug. 4, 2009] p. 47-p. 48; p. 50-p. 51. |
Panella, et al., “An RNS Architecture for Quasi-Chaotic Oscillators” The Journal of VLSI Signal Processing, Kluwer Academic Publishes, BO, vol. 33, No. 1-2, Jan. 1, 2003, pp. 199-220, XP019216547, ISSN: 1573-109X. |
Pleszczynski, S, “On the Generation of Permutations” Information Processing Letters, Amsterdam, NL, vol. 3, No. 6, Jul. 1, 1975, pp. 180-183, XP008023810, ISSN: 0020-0190. |
Pourbigharaz F. et al, Modulo-Free Architecture for Binary to Residue Transformation with Respect to (2m−1, 2m, 2m+1) Moduli Set, IEEE International Symposium on Circuits and Systems, May 30-Jun. 2, 1994, pp. 317-320, vol. 2, London, UK. |
Salberg, et al, “Stochastic multipulse-PAM: A subspace modulation technique with diversity” Signal Processing, Elsevier Science Publishers B.V. Amsterdam, NL, vol. 83, No. 12, Dec. 1, 2003, pp. 2559-2577, XP004467986; ISSN: 0165-1684. |
Vanwiggeren, et al., “Chaotic Communication Using Time-Delayed Optical Systems,” International Journal of Bifurcation and Chaos, vol. 9, No. 11, (1999) pp. 2129-2156, World Scientific Publishing Co. |
Weisstein, Eric W., “Injection,” From MathWorld—A Wolfram Web Resource. http://mathworld.wolfram.com/Injection.html. |
Weisstein, Eric W. “Surjection,” From MathWorld—A Wolfram Web Resource, http://mathworld.wolfram.com/Surjection.html. |
Yen, et al., (1999) “Residual Number System Assisted CDMA: A New System Concept”, In: ACTS'99, Jun. 8-11, 1999, Sorrento, Italy. |
Yu, et al., “A comparative Study of Different Chaos Based Spread Spectrum Communication Systems”, ISCAS 2001, Proceedings of the 2001 IEEE International Symposium on Circuits and Systems, Sydney, Australia, May 6-9, 2001; (IEEE International Symposium on Circuits and Systems], New York, NY : IEEE, US, vol. 3, May 6, 2001, pp. 216-216, XP01054114, ISBN: 978-0-7803-6685-5. |
Michaels, et al., U.S. Appl. No. 12/496,214, filed Jul. 1, 2009, entitled “Anti-Jam Communications Having Selectively Variable PAPR Including Cazac Waveform”. |
Michaels, et al., U.S. Appl. No. 12/507,111, filed Jul. 22, 2009, entitled “Anti-Jam Communications Using Adaptive Chaotic Spread Waveform”. |
Chester, et al., U.S. Appl. No. 12/480,264, filed Jun. 8, 2009, entitled “Continuous Time Chaos Dithering”. |
Chester, et al., U.S. Appl. No. 12/481,704, filed Jun. 10, 2009, entitled “Discrete Time Chaos Dithering”. |
Michaels, et al., U.S. Appl. No. 12/345,163, filed Dec. 29, 2008, entitled “Communications System Employing Chaotic Spreading Codes With Static Offsets”. |
Micheals, et al., U.S. Appl. No. 12/344,962, filed Dec. 29, 2008, entitled “Communications System Employing Orthogonal Chaotic Spreading Codes”. |
Michaels, et al., U.S. Appl. No. 12/396,828, filed Jun. 3, 2009, entitled “Communications System Employing Orthogonal Chaotic Spreading Codes”. |
Michaels, et al., U.S. Appl. No. 12/496,170, filed Jul. 1, 2009, entitled “Permission Based Multiple Access Communications Systems”. |
Michaels, et al., U.S. Appl. No. 12/496,233, filed Jul. 1, 2009, entitled “Permission-Based Secure Multiple Access Communication Systems Rotations”. |
Michaels, et al., U.S. Appl. No. 12/507,512, filed Jul. 22, 2009, entitled “Permission-Based TDMA Chaotic Communication Systems”. |
Micheals, et al., U.S. Appl. No. 12/496,085, filed Jul. 1, 2009, entitled, “High-Speed Cryptographic System Using Chaotic Sequences”. |
Michaels, et al., U.S. Appl. No. 12/496,123, filed Jul. 1, 2009, entitled, “Rake Receiver for Spread Spectrum Chaotic Communications Systems”. |
Michaels, et al., U.S. Appl. No. 12/496,146, filed Jul. 1, 2009, entitled “Improved Symbol Estimation for Chaotic Spread Spectrum Signal”. |
Micheals, et al., U.S. Appl. No. 12/480,316, filed Jun. 8, 2009, entitled “Symbol Duration Dithering for Secured Chaotic Communications”. |
Michaels, et al., U.S. Appl. No. 12/496,183, filed Jul. 1, 2009, entitled “Bit Error Rate Reduction in Chaotic Communications”. |
Michaels, Alan, U.S. Appl. No. 12/248,131, filed Oct. 9, 2008, entitled “AD-HOC Network Acquisition Using Chaotic Sequence Spread Waveform”. |
Michaels, Alan, U.S. Appl. No. 12/201,021, filed Aug. 29, 2008, entitled, “Multi-Tier AD-HOC Network Communications”. |
Taylor, F.J., “Residue Arithmetic a Tutorial with Examples”, Computer, vol. 17, No. 5, pp. 50-62, May 1984, doi: 10.1109/MC. 1984.1659138. |
Barda, A; et al., “Chaotic signals for multiple access communications,” Electrical and Electronics Engineers in Israel, 1995, Eighteenth Convention of, vol., No., pp. 2.1.3/1-2.1/3/5, Mar. 7-8, 1995. |
Alia, G., et al., “A VLSI Algorithm for Direct and Reverse Conversion from Weighted Binary Number System to Residue Number System”, IEEE Trans on Circuits and Systems, vol. Cas-31, No. 12, Dec. 1984. |
Information about Related Patents and Patent Applications, see Section 6 of the accompanying Information Disclosure Statement Letter, which concerns Related Patents and Patent Applications. |
Menezes, Vanstone, Oorschot: “Handbook of Applied Cryptography”, 1997, CRC Press LLC, USA, XP002636791, p. 80-p. 85, p. 238-242. |
Schneier, Bruce: “Applied Cryptography Second Edition”, 1997, John Wiley & Sons, USA, XP002636792, p. 254-p. 255. |
Office Action issued in Japanese Patent Application No. 2010-504206 in the name of Harris Corporation; mailed Jan. 6, 2012. |
Bender, et al., “Techniques for data hiding”, 1995, IBM Systems Journal, vol. 35, pp. 313-336. |
Japanese Office Action dated Aug. 29, 2012, Application Serial No. 2011-531166 in the name of Harris Corporation. |
Number | Date | Country | |
---|---|---|---|
20110004792 A1 | Jan 2011 | US |